Association of Socioeconomic Area Deprivation Index with Hospital Readmissions After Colon and Rectal Surgery

Abstract

Background

Risk adjustment for reimbursement and quality measures omits social risk factors despite adversely affecting health outcomes. Social risk factors are not usually available in electronic health records (EHR) or administrative data. Socioeconomic status can be assessed by using US Census data. Distressed Communities Index (DCI) is based upon zip codes, and the Area Deprivation Index (ADI) provides more granular estimates at the block group level. We examined the association of neighborhood disadvantage using the ADI, DCI, and patient-level insurance status on 30-day readmission risk after colorectal surgery.

Methods

Our 677 patient cohort was derived from the 2013–2017 National Surgical Quality Improvement Program at a safety net hospital augmented with EHR data to determine insurance status and 30-day readmissions. Patients’ home addresses were linked to the ADI and DCI.

Results

Our cohort consisted of 53.9% males and 63.8% Hispanics with a 22.9% 30-day readmission rate from the date of discharge; > 50% lived in highly deprived neighborhoods. Controlling for medical comorbidities and complications, ADI was associated with increased risk of 30 days from the date of discharge readmissions among patients living in medium (OR = 2.15, p = .02) or high (OR = 1.88, p = .03) deprived areas compared to less-deprived neighborhoods, but not insurance status or DCI.

Conclusions

The ADI identified patients living in deprived communities with increased readmission risk. Our results show that block-group level ADI can potentially be used in risk adjustment, to identify high-risk patients and to design better care pathways that improve health outcomes.

Introduction

Colorectal operations are among the most common surgeries performed in the USA and are associated with one of the highest rates of complications and hospital readmissions of general surgery procedures.^1,2 The Hospital Readmissions Reduction Program (HRRP) mandates financial penalties for higher than expected 30-day readmission rates. The HRRP’s unintended consequences of disproportionately penalizing safety net hospitals (SNHs) constrain resources at hospitals caring for the most vulnerable populations.^3–7 A study across four states showed a 30-day readmission rate for colectomy patients of 10.9% that increased to 12.1% in the subgroup of hospitals with a high safety net burden.⁸ The Centers for Medicare & Medicaid Services (CMS) recently established a new peer group-based payment adjustment system for assessing readmission penalties comparing similar hospitals stratified by patient socioeconomic status (SES) measured by the proportion of patients with dual enrollment in Medicare/Medicaid. The greatest penalty reductions occurred in hospitals serving the lowest SES patients, lessening, but not eliminating, the previously unbalanced penalty burden for SNH.⁹

Patient-level SES variables that could improve risk adjustment are limited in administrative data and electronic health records (EHR). However, and despite known limitations, dual enrollment in Medicare/Medicaid, insurances status,² and race and ethnicity are commonly used measures to identify health disparities and low SES populations.¹⁰ Another commonly used patient characteristic is their zip code linked to US Census data to estimate individual-level SES, usually showing no or mixed effects on outcomes^11–15 due to the lack of granularity. US Census Zip Code Tabulation Areas are generalized representations of zip codes with an average population of 9414. The National Academy of Medicine released five reports outlining the need to develop better risk-adjustment methods using more granular social risk factor data.¹⁶ A more granular proxy measure is the “block group” representing approximately 1431 residents.¹⁷

The Area Deprivation Index (ADI) and Distressed Communities Index (DCI) were developed to help identify populations living in deprived/disadvantaged neighborhoods. The ADI¹⁸ uses 17 American Community Survey¹⁹ variables from the US Census to stratify geographic areas based on socioeconomic disadvantage at the more granular block group level. Patients living in more compared with less disadvantaged neighborhoods had higher 30-day all-cause readmissions.^18,20,21 The DCI combines five measures from the American Community Survey and two measures from the US Census Bureau Business Patterns dataset to estimate the community socioeconomic distress by zip codes.²² Several recent studies merged DCI with the American College of Surgeons National Quality Improvement Program (NSQIP)^23–26 data improving prediction of postoperative complications and risk adjustment.^27–31 Using ADI data provides more granularity but requires patient addresses to be geocoded, while DCI can be easily linked to patients using their zip codes but provides data on a less granular level.

Comparing studies on the effect of social risk factors on readmission risk is further complicated by the variability in defining 30-day readmissions. Many studies using NSQIP data define readmissions as 30 days from the date of surgery while the CMS defines readmissions as 30 days from the date of discharge from the index procedure. The goals of our study are to (1) examine ADI, DCI, and insurance status as proxy SES measures to predict 30-day readmissions after colorectal surgery and (2) use both definitions of 30-day readmissions in models using ADI, DCI, and insurance status. We hypothesize that patients living in distressed/deprived neighborhoods have an increased risk of 30-day readmissions and that using the more granular ADI will provide increased sensitivity in predicting readmission risk than the DCI or insurance status.